@article{,

title = {Mapping the denominator: spatial demography in the measurement of progress},

author = {Andrew J. Tatem},

url = {https://academic.oup.com/inthealth/article/6/3/153/2964850},

issn = {1876-3413},

year  = {2014},

date = {2014-01-01},

urldate = {2014-01-01},

journal = {International Health},

volume = {6},

number = {3},

pages = {153-155},

abstract = {Measuring progress towards international health goals requires a reliable baseline from which to measure change and recent methodological advancements have advanced our abilities to measure, model and map the prevalence of health issues using sophisticated tools. The provision of burden estimates generally requires linking these estimates with spatial demographic data, but for many resource-poor countries data on total population sizes, distributions, compositions and temporal trends are lacking, prompting a reliance on uncertain estimates. Modern technologies and data archives are offering solutions, but the huge range of uncertainties that exist today in spatial denominator datasets will still be around for many years to come.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pindolia2013,

title = {The demographics of human and malaria movement and migration patterns in East Africa},

author = {Deepa K. Pindolia and Andres J. Garcia and Zhuojie Huang and David L. Smith and Victor A. Alegana and Abdisalan M. Noor and Robert W. Snow and Andrew J. Tatem},

url = {https://doi.org/10.1186/1475-2875-12-397},

doi = {10.1186/1475-2875-12-397},

issn = {1475-2875},

year  = {2013},

date = {2013-11-05},

journal = {Malaria Journal},

volume = {12},

number = {1},

pages = {397},

abstract = {The quantification of parasite movements can provide valuable information for control strategy planning across all transmission intensities. Mobile parasite carrying individuals can instigate transmission in receptive areas, spread drug resistant strains and reduce the effectiveness of control strategies. The identification of mobile demographic groups, their routes of travel and how these movements connect differing transmission zones, potentially enables limited resources for interventions to be efficiently targeted over space, time and populations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lu2013,

title = {Approaching the Limit of Predictability in Human Mobility},

author = {Xin Lu and Erik Wetter and Nita Bharti and Andrew J. Tatem and Linus Bengtsson},

url = {https://doi.org/10.1038/srep02923},

doi = {10.1038/srep02923},

issn = {2045-2322},

year  = {2013},

date = {2013-10-11},

journal = {Scientific Reports},

volume = {3},

number = {1},

pages = {2923},

abstract = {In this study we analyze the travel patterns of 500,000 individuals in Cote d'Ivoire using mobile phone call data records. By measuring the uncertainties of movements using entropy, considering both the frequencies and temporal correlations of individual trajectories, we find that the theoretical maximum predictability is as high as 88%. To verify whether such a theoretical limit can be approached, we implement a series of Markov chain (MC) based models to predict the actual locations visited by each user. Results show that MC models can produce a prediction accuracy of 87% for stationary trajectories and 95% for non-stationary trajectories. Our findings indicate that human mobility is highly dependent on historical behaviors and that the maximum predictability is not only a fundamental theoretical limit for potential predictive power, but also an approachable target for actual prediction accuracy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tatem2013,

title = {Millennium development health metrics: where do Africa's children and women of childbearing age live?},

author = {Andrew J. Tatem and Andres J. Garcia and Robert W. Snow and Abdisalan M. Noor and Andrea E. Gaughan and Marius Gilbert and Catherine Linard},

url = {https://doi.org/10.1186/1478-7954-11-11},

doi = {10.1186/1478-7954-11-11},

issn = {1478-7954},

year  = {2013},

date = {2013-07-23},

journal = {Population Health Metrics},

volume = {11},

number = {1},

pages = {11},

abstract = {The Millennium Development Goals (MDGs) have prompted an expansion in approaches to deriving health metrics to measure progress toward their achievement. Accurate measurements should take into account the high degrees of spatial heterogeneity in health risks across countries, and this has prompted the development of sophisticated cartographic techniques for mapping and modeling risks. Conversion of these risks to relevant population-based metrics requires equally detailed information on the spatial distribution and attributes of the denominator populations. However, spatial information on age and sex composition over large areas is lacking, prompting many influential studies that have rigorously accounted for health risk heterogeneities to overlook the substantial demographic variations that exist subnationally and merely apply national-level adjustments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tatem2013b,

title = {Urbanization and the global malaria recession},

author = {Andrew J. Tatem and Peter W. Gething and David L. Smith and Simon I. Hay},

url = {https://doi.org/10.1186/1475-2875-12-133},

doi = {10.1186/1475-2875-12-133},

issn = {1475-2875},

year  = {2013},

date = {2013-04-17},

journal = {Malaria Journal},

volume = {12},

number = {1},

pages = {133},

abstract = {The past century has seen a significant contraction in the global extent of malaria transmission, resulting in over 50 countries being declared malaria free, and many regions of currently endemic countries eliminating the disease. Moreover, substantial reductions in transmission have been seen since 1900 in those areas that remain endemic today. Recent work showed that this malaria recession was unlikely to have been driven by climatic factors, and that control measures likely played a significant role. It has long been considered, however, that economic development, and particularly urbanization, has also been a causal factor. The urbanization process results in profound socio-economic and landscape changes that reduce malaria transmission, but the magnitude and extent of these effects on global endemicity reductions are poorly understood.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cohen2013,

title = {Rapid case-based mapping of seasonal malaria transmission risk for strategic elimination planning in Swaziland},

author = {Justin M. Cohen and Sabelo Dlamini and Joseph M. Novotny and Deepika Kandula and Simon Kunene and Andrew J. Tatem},

url = {https://doi.org/10.1186/1475-2875-12-61},

doi = {10.1186/1475-2875-12-61},

issn = {1475-2875},

year  = {2013},

date = {2013-02-11},

journal = {Malaria Journal},

volume = {12},

number = {1},

pages = {61},

abstract = {As successful malaria control programmes move towards elimination, they must identify residual transmission foci, target vector control to high-risk areas, focus on both asymptomatic and symptomatic infections, and manage importation risk. High spatial and temporal resolution maps of malaria risk can support all of these activities, but commonly available malaria maps are based on parasite rate, a poor metric for measuring malaria at extremely low prevalence. New approaches are required to provide case-based risk maps to countries seeking to identify remaining hotspots of transmission while managing the risk of transmission from imported cases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1371/journal.pone.0055882,

title = {High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015},

author = {Andrea E. Gaughan and Forrest R. Stevens and Catherine Linard and Peng Jia and Andrew J. Tatem},

url = {https://doi.org/10.1371/journal.pone.0055882},

doi = {10.1371/journal.pone.0055882},

year  = {2013},

date = {2013-01-01},

journal = {PLOS ONE},

volume = {8},

number = {2},

pages = {1-11},

publisher = {Public Library of Science},

abstract = {Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1371/journal.pone.0056057,

title = {Place-Based Attributes Predict Community Membership in a Mobile Phone Communication Network},

author = {T. Trevor Caughlin and Nick Ruktanonchai and Miguel A. Acevedo and Kenneth K. Lopiano and Olivia Prosper and Nathan Eagle and Andrew J. Tatem},

url = {https://doi.org/10.1371/journal.pone.0056057},

doi = {10.1371/journal.pone.0056057},

year  = {2013},

date = {2013-01-01},

journal = {PLOS ONE},

volume = {8},

number = {2},

pages = {1-9},

publisher = {Public Library of Science},

abstract = {Social networks can be organized into communities of closely connected nodes, a property known as modularity. Because diseases, information, and behaviors spread faster within communities than between communities, understanding modularity has broad implications for public policy, epidemiology and the social sciences. Explanations for community formation in social networks often incorporate the attributes of individual people, such as gender, ethnicity or shared activities. High modularity is also a property of large-scale social networks, where each node represents a population of individuals at a location, such as call flow between mobile phone towers. However, whether or not place-based attributes, including land cover and economic activity, can predict community membership for network nodes in large-scale networks remains unknown. We describe the pattern of modularity in a mobile phone communication network in the Dominican Republic, and use a linear discriminant analysis (LDA) to determine whether geographic context can explain community membership. Our results demonstrate that place-based attributes, including sugar cane production, urbanization, distance to the nearest airport, and wealth, correctly predicted community membership for over 70% of mobile phone towers. We observed a strongly positive correlation (r = 0.97) between the modularity score and the predictive ability of the LDA, suggesting that place-based attributes can accurately represent the processes driving modularity. In the absence of social network data, the methods we present can be used to predict community membership over large scales using solely place-based attributes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1371/journal.pone.0052971,

title = {The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales},

author = {Amy Wesolowski and Caroline O. Buckee and Deepa K. Pindolia and Nathan Eagle and David L. Smith and Andres J. Garcia and Andrew J. Tatem},

url = {https://doi.org/10.1371/journal.pone.0052971},

doi = {10.1371/journal.pone.0052971},

year  = {2013},

date = {2013-01-01},

journal = {PLOS ONE},

volume = {8},

number = {1},

pages = {1-8},

publisher = {Public Library of Science},

abstract = {Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LINARD201323,

title = {Modelling spatial patterns of urban growth in Africa},

author = {Catherine Linard and Andrew J. Tatem and Marius Gilbert},

url = {https://www.sciencedirect.com/science/article/pii/S0143622813001707},

doi = {https://doi.org/10.1016/j.apgeog.2013.07.009},

issn = {0143-6228},

year  = {2013},

date = {2013-01-01},

journal = {Applied Geography},

volume = {44},

pages = {23-32},

abstract = {The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.},

keywords = {Africa, Boosted regression trees, Modelling, Spatial pattern, Urban growth},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1098/rsif.2012.0756,

title = {Implications of spatially heterogeneous vaccination coverage for the risk of congenital rubella syndrome in South Africa},

author = {C. J. E. Metcalf and C. Cohen and J. Lessler and J. M. McAnerney and G. M. Ntshoe and A. Puren and P. Klepac and A. Tatem and B. T. Grenfell and O. N. Bjørnstad},

url = {https://royalsocietypublishing.org/doi/abs/10.1098/rsif.2012.0756},

doi = {10.1098/rsif.2012.0756},

year  = {2013},

date = {2013-01-01},

journal = {Journal of The Royal Society Interface},

volume = {10},

number = {78},

pages = {20120756},

abstract = {Rubella is generally a mild childhood disease, but infection during early pregnancy may cause spontaneous abortion or congenital rubella syndrome (CRS), which may entail a variety of birth defects. Since vaccination at levels short of those necessary to achieve eradication may increase the average age of infection, and thus potentially the CRS burden, introduction of the vaccine has been limited to contexts where coverage is high. Recent work suggests that spatial heterogeneity in coverage should also be a focus of concern. Here, we use a detailed dataset from South Africa to explore the implications of heterogeneous vaccination for the burden of CRS, introducing realistic vaccination scenarios based on reported levels of measles vaccine coverage. Our results highlight the potential impact of country-wide reductions of incidence of rubella on the local CRS burdens in districts with small population sizes. However, simulations indicate that if rubella vaccination is introduced with coverage reflecting current estimates for measles coverage in South Africa, the burden of CRS is likely to be reduced overall over a 30 year time horizon by a factor of 3, despite the fact that this coverage is lower than the traditional 80 per cent rule of thumb for vaccine introduction, probably owing to a combination of relatively low birth and transmission rates. We conclude by discussing the likely impact of private-sector vaccination.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1098/rstb.2012.0145,

title = {A sticky situation: the unexpected stability of malaria elimination},

author = {David L. Smith and Justin M. Cohen and Christinah Chiyaka and Geoffrey Johnston and Peter W. Gething and Roly Gosling and Caroline O. Buckee and Ramanan Laxminarayan and Simon I. Hay and Andrew J. Tatem},

url = {https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2012.0145},

doi = {10.1098/rstb.2012.0145},

year  = {2013},

date = {2013-01-01},

journal = {Philosophical Transactions of the Royal Society B: Biological Sciences},

volume = {368},

number = {1623},

pages = {20120145},

abstract = {Malaria eradication involves eliminating malaria from every country where transmission occurs. Current theory suggests that the post-elimination challenges of remaining malaria-free by stopping transmission from imported malaria will have onerous operational and financial requirements. Although resurgent malaria has occurred in a majority of countries that tried but failed to eliminate malaria, a review of resurgence in countries that successfully eliminated finds only four such failures out of 50 successful programmes. Data documenting malaria importation and onwards transmission in these countries suggests malaria transmission potential has declined by more than 50-fold (i.e. more than 98%) since before elimination. These outcomes suggest that elimination is a surprisingly stable state. Elimination's ‘stickiness’ must be explained either by eliminating countries starting off qualitatively different from non-eliminating countries or becoming different once elimination was achieved. Countries that successfully eliminated were wealthier and had lower baseline endemicity than those that were unsuccessful, but our analysis shows that those same variables were at best incomplete predictors of the patterns of resurgence. Stability is reinforced by the loss of immunity to disease and by the health system's increasing capacity to control malaria transmission after elimination through routine treatment of cases with antimalarial drugs supplemented by malaria outbreak control. Human travel patterns reinforce these patterns; as malaria recedes, fewer people carry malaria from remote endemic areas to remote areas where transmission potential remains high. Establishment of an international resource with backup capacity to control large outbreaks can make elimination stickier, increase the incentives for countries to eliminate, and ensure steady progress towards global eradication. Although available evidence supports malaria elimination's stickiness at moderate-to-low transmission in areas with well-developed health systems, it is not yet clear if such patterns will hold in all areas. The sticky endpoint changes the projected costs of maintaining elimination and makes it substantially more attractive for countries acting alone, and it makes spatially progressive elimination a sensible strategy for a malaria eradication endgame.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Qi2012,

title = {The effects of urbanization on global Plasmodium vivax malaria transmission},

author = {Qiuyin Qi and Carlos A. Guerra and Catherine L. Moyes and Iqbal AR F. Elyazar and Peter W. Gething and Simon I. Hay and Andrew J. Tatem},

url = {https://doi.org/10.1186/1475-2875-11-403},

doi = {10.1186/1475-2875-11-403},

issn = {1475-2875},

year  = {2012},

date = {2012-12-05},

journal = {Malaria Journal},

volume = {11},

number = {1},

pages = {403},

abstract = {Many recent studies have examined the impact of urbanization on Plasmodium falciparum malaria endemicity and found a general trend of reduced transmission in urban areas. However, none has examined the effect of urbanization on Plasmodium vivax malaria, which is the most widely distributed malaria species and can also cause severe clinical syndromes in humans. In this study, a set of 10,003 community-based P. vivax parasite rate (Pv PR) surveys are used to explore the relationships between Pv PR in urban and rural settings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pindolia2012,

title = {Human movement data for malaria control and elimination strategic planning},

author = {Deepa K. Pindolia and Andres J. Garcia and Amy Wesolowski and David L. Smith and Caroline O. Buckee and Abdisalan M. Noor and Robert W. Snow and Andrew J. Tatem},

url = {https://doi.org/10.1186/1475-2875-11-205},

doi = {10.1186/1475-2875-11-205},

issn = {1475-2875},

year  = {2012},

date = {2012-06-18},

journal = {Malaria Journal},

volume = {11},

number = {1},

pages = {205},

abstract = {Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tatem2012,

title = {Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation},

author = {Andrew J. Tatem and Susana Adamo and Nita Bharti and Clara R. Burgert and Marcia Castro and Audrey Dorelien and Gunter Fink and Catherine Linard and Mendelsohn John and Livia Montana and Mark R. Montgomery and Andrew Nelson and Abdisalan M. Noor and Deepa Pindolia and Greg Yetman and Deborah Balk},

url = {https://doi.org/10.1186/1478-7954-10-8},

doi = {10.1186/1478-7954-10-8},

issn = {1478-7954},

year  = {2012},

date = {2012-05-16},

journal = {Population Health Metrics},

volume = {10},

number = {1},

pages = {8},

abstract = {The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Linard2012,

title = {Large-scale spatial population databases in infectious disease research},

author = {Catherine Linard and Andrew J. Tatem},

url = {https://doi.org/10.1186/1476-072X-11-7},

doi = {10.1186/1476-072X-11-7},

issn = {1476-072X},

year  = {2012},

date = {2012-03-20},

journal = {International Journal of Health Geographics},

volume = {11},

number = {1},

pages = {7},

abstract = {Modelling studies on the spatial distribution and spread of infectious diseases are becoming increasingly detailed and sophisticated, with global risk mapping and epidemic modelling studies now popular. Yet, in deriving populations at risk of disease estimates, these spatial models must rely on existing global and regional datasets on population distribution, which are often based on outdated and coarse resolution data. Moreover, a variety of different methods have been used to model population distribution at large spatial scales. In this review we describe the main global gridded population datasets that are freely available for health researchers and compare their construction methods, and highlight the uncertainties inherent in these population datasets. We review their application in past studies on disease risk and dynamics, and discuss how the choice of dataset can affect results. Moreover, we highlight how the lack of contemporary, detailed and reliable data on human population distribution in low income countries is proving a barrier to obtaining accurate large-scale estimates of population at risk and constructing reliable models of disease spread, and suggest research directions required to further reduce these barriers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1126/science.1229045,

title = {Optimizing Investments in Malaria Treatment and Diagnosis},

author = {Justin M. Cohen and Aaron M. Woolsey and Oliver J. Sabot and Peter W. Gething and Andrew J. Tatem and Bruno Moonen},

url = {https://www.science.org/doi/abs/10.1126/science.1229045},

doi = {10.1126/science.1229045},

year  = {2012},

date = {2012-01-01},

journal = {Science},

volume = {338},

number = {6107},

pages = {612-614},

abstract = {Better targeting of antimalarials to people who need them will maximize the impact of interventions in the private sector. The Roll Back Malaria (RBM) Partnership has set an ambitious target of achieving near zero deaths from malaria by 2015 (1). Scale-up of insecticide-treated nets, indoor residual spraying of insecticide, and increased access to treatment with artemisinin-based combination therapies (ACTs) over the past decade have led to reductions in malaria incidence of more than 50% in 43 countries, including 8 in Africa (2). However, as an estimated 655,000 malaria deaths still occurred in 2010 (2), with the great majority in sub-Saharan Africa, substantial challenges remain.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1126/science.1223467,

title = {Quantifying the Impact of Human Mobility on Malaria},

author = {Amy Wesolowski and Nathan Eagle and Andrew J. Tatem and David L. Smith and Abdisalan M. Noor and Robert W. Snow and Caroline O. Buckee},

url = {https://www.science.org/doi/abs/10.1126/science.1223467},

doi = {10.1126/science.1223467},

year  = {2012},

date = {2012-01-01},

journal = {Science},

volume = {338},

number = {6104},

pages = {267-270},

abstract = {An obstacle to developing effective national malaria control programs is a lack of understanding of human movements, which are an important component of disease transmission. As mobile phones have become increasingly ubiquitous, it is now possible to collect individual-level, longitudinal data on human movements on a massive scale. Wesolowski et al. (p. 267) analyzed mobile phone call data records representing the travel patterns of 15 million mobile phone owners in Kenya over the course of a year. This was combined with a detailed malaria risk map, to estimate malaria parasite movements across the country that could be caused by human movement. This information enabled detailed analysis of parasite sources and sinks between hundreds of local settlements. Estimates were compared with hospital data from Nairobi to show that local pockets of transmission likely occur around the periphery of Nairobi, accounting for locally acquired cases, contrary to the accepted idea that there is no transmission in the capital. Geographical information in mobile phone records for 15 million Kenyans is linked to malaria prevalence estimates. Human movements contribute to the transmission of malaria on spatial scales that exceed the limits of mosquito dispersal. Identifying the sources and sinks of imported infections due to human travel and locating high-risk sites of parasite importation could greatly improve malaria control programs. Here, we use spatially explicit mobile phone data and malaria prevalence information from Kenya to identify the dynamics of human carriers that drive parasite importation between regions. Our analysis identifies importation routes that contribute to malaria epidemiology on regional spatial scales.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.1371/journal.pone.0031743,

title = {Population Distribution, Settlement Patterns and Accessibility across Africa in 2010},

author = {Catherine Linard and Marius Gilbert and Robert W. Snow and Abdisalan M. Noor and Andrew J. Tatem},

url = {https://doi.org/10.1371/journal.pone.0031743},

doi = {10.1371/journal.pone.0031743},

year  = {2012},

date = {2012-01-01},

journal = {PLOS ONE},

volume = {7},

number = {2},

pages = {1-8},

publisher = {Public Library of Science},

abstract = {The spatial distribution of populations and settlements across a country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accurately measure population concentration and accessibility. Here we outline approaches to developing a new high resolution population distribution dataset for Africa and analyse rural accessibility to population centers. Contemporary population count data were combined with detailed satellite-derived settlement extents to map population distributions across Africa at a finer spatial resolution than ever before. Substantial heterogeneity in settlement patterns, population concentration and spatial accessibility to major population centres is exhibited across the continent. In Africa, 90% of the population is concentrated in less than 21% of the land surface and the average per-person travel time to settlements of more than 50,000 inhabitants is around 3.5 hours, with Central and East Africa displaying the longest average travel times. The analyses highlight large inequities in access, the isolation of many rural populations and the challenges that exist between countries and regions in providing access to services. The datasets presented are freely available as part of the AfriPop project, providing an evidence base for guiding strategic decisions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Linard2011,

title = {Assessing the use of global land cover data for guiding large area population distribution modelling},

author = {Catherine Linard and Marius Gilbert and Andrew J. Tatem},

url = {https://doi.org/10.1007/s10708-010-9364-8},

doi = {10.1007/s10708-010-9364-8},

issn = {1572-9893},

year  = {2011},

date = {2011-10-01},

journal = {GeoJournal},

volume = {76},

number = {5},

pages = {525-538},

abstract = {Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover data, thus restricting application of the approach to this region. If gridded population data are to be improved across Africa, an alternative, consistent and comparable source of land cover data is required. Here these analyses were repeated for Kenya using four continent-wide land cover datasets combined with detailed settlement extents and accuracies were assessed against detailed census data. The aim was to identify the large area land cover dataset that, combined with detailed settlement extents, produce the most accurate population distribution data. The effectiveness of the population distribution modelling procedures in the absence of high resolution census data was evaluated, as was the extrapolation ability of population densities between different regions. Results showed that the use of the GlobCover dataset refined with detailed settlement extents provided significantly more accurate gridded population data compared to the use of refined AVHRR-derived, MODIS-derived and GLC2000 land cover datasets. This study supports the hypothesis that land cover information is important for improving population distribution model accuracies, particularly in countries where only coarse resolution census data are available. Obtaining high resolution census data must however remain the priority. With its higher spatial resolution and its more recent data acquisition, the GlobCover dataset was found as the most valuable resource to use in combination with detailed settlement extents for the production of gridded population datasets across large areas.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}